Semantic Graph & Ontology Architect
Rubicon Consulting
Rubicon Consulting is currently recruiting for Semantic Graph & Ontology Architect on a 6 Month Rolling Contract, based in Warwickshire.
Role Summary
We’re building a Smart Data Fabric that unifies enterprise data (Snowflake, SharePoint, ERP, NoSQL, and document silos) and exposes it to advanced AI agents through a semantic, graph-native, and vector-aware foundation. You will own graph and semantic architecture, modeling business relationships, processes, and logic to enable accurate, contextual, auditable workflows. This is a hands-on leadership role spanning LPG vs RDF/OWL tradeoffs, query optimization, and ontology engineering.
Key Responsibilities
Graph & Semantic Architecture
- Design scalable graph schemas (LPG and/or RDF/OWL) based on semantic and inference requirements.
- Author and optimize Cypher/Gremlin/SPARQL queries for multi-hop traversal, orchestration, and complex reasoning.
- Define canonical entity models and mapping layers across Snowflake, MongoDB, SharePoint, ERP, and unstructured content.
Ontology Engineering & Reasoning
- Create and maintain formal ontologies/taxonomies; govern versioning and lifecycle.
- Implement logical inference (rules/constraints) for agent decision-making, conflict detection, and workflow integrity.
- Establish semantic consistency standards and data quality checks.
Hybrid Semantic Layer (Graph + Logic)
- Design a hybrid semantic layer combining graph context with business logic and access controls for semantic search, multi-hop traversal, and knowledge contextualization.
- Model RACI/RBAC as graph edges/nodes; embed compliance rules and auditability.
APIs, Patterns & Collaboration
- Define clean API layers for semantic enrichment and retrieval; deliver reference implementations and patterns.
- Specify MCP-based (Model Context Protocol) tool discovery/invocation patterns; collaborate with platform engineers for agent connectivity.
- Partner with data/platform/security teams on ingestion pipelines, lineage, governance, and observability requirements.
Quality, Performance & Governance
- Set query performance budgets; prevent Cartesian explosions; ensure index utilization.
- Establish lineage and data governance artifacts (semantic catalogs, policy nodes, audit trails).
- Document standards and mentor engineers adopting graph/semantic patterns.
Requirements
- Bachelor’s/Master’s in CS, Data Science, Mathematics, Engineering, or related field.
- 7–12 years in graph databases, semantic modelling, ontology engineering.
- Deep expertise in Cypher, Gremlin, SPARQL; strong command of LPG vs RDF/OWL tradeoffs.
- Hands-on with Neo4j, AWS Neptune, TigerGraph, Stardog (at least one in production).
- Experience mapping enterprise data (Snowflake/MongoDB/SharePoint/ERP) into graph/ontology layers.
- Strong understanding of RBAC/RACI, data governance, lineage, and security controls.
- Ability to design clean APIs and reference implementations for semantic enrichment/retrieval.
- Practical AWS familiarity (IAM, VPC, S3, EKS/ECS/Lambda) in collaboration with platform teams.
Preferred Qualifications
- Ontology tooling (Protégé, SHACL/SWRL), reasoning engines, and constraint modeling.
- Prior delivery of enterprise knowledge graphs supporting workflows & audit trails.
- Exposure to vector retrieval/RAG and how graph context informs re-ranking.
- Observability awareness (tracing across graph layers, OpenTelemetry, Prometheus/Grafana).
- Experience with Snowflake/MongoDB/SharePoint APIs and ERP data structures
Our Company
Rubicon Consulting is a Talent management consultancy which helps you to optimise business performance and competitive advantage by choosing the right people first time!
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